Exclusive Content &amp Downloads from ASQ

Summary:
This comment focuses on the first part of an article by Picheny et al. (Victor Picheny, David Ginsbourger, Yann Richet, and Gregory Caplin, Quantile-Based Optimization of Noisy Computer Experiments with Tunable Precision, Technometrics, 55-1, pages 29-31), regarding the modeling of computer experiments with tunable precision. The comment proposes a sequential sampling plan for stochastic simulation with tunable precision, which allows more data to be collected for the same computational budget. The authors have also introduced a Brownian motion kriging model, which can be used to fit the data from the proposed sampling plan. Some mathematical justification of the proposed model is given.

Anyone with a subscription, including Site and Enterprise members, can access this article.